Estimating the contribution of groundwater to rootzone soil moisture
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the Huaibei Plain basin, China, soybean is a main crop. During the soybean growth period, rainfall can vary largely and depth to watertable can also vary largely. The amount of water supplied to the soybean rootzone by groundwater affects soybean growth and yield. Accurate simulation of groundwater contributions to soybean rootzone soil moisture (groundwater contribution) can be important for determining irrigation to and drainage from soybean fields. Based on field observations and local weather data of 2005, HYDRUS-1D was validated by comparing simulated and measured rootzone soil water contents. The validated model was used to estimate the daily groundwater contributions for three different soybean hydrological growing seasons, i.e., an average year (1997), a wet year (2005), and a dry year (2004) with soybean growth at its optimal state. The main results were: (1) seasonal groundwater contribution was 157 mm in the experimental field, and the estimated groundwater contributions were 158, 222, and 387 mm in the wet, average, and dry seasons, respectively; (2) the groundwater contribution was about 63% of the total seasonal transpiration in the experimental field, and those were about 142, 80, and 66% of the total seasonal transpiration in dry, average, and wet seasons, respectively.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it